Replacing liver cancer models by modeling human liver cancer in vitro

Liver cancer is among the most lethal cancers. This is because at present, there is only an elemental understanding of the pathogenesis and imited therapeutic options. This is in part due to the lack of good models that faithfully represent the genetic variability of human liver cancer. In fact, the majority of the existing animal models (from mice to dog) do not replicate the human disease and existing cell lines do not mimic the complex genetic variability of these tumours. Only Patient Derived Xenografts (PDXs) retain all the patient's tumour characteristics, from their histological architecture to their transcriptome, methylome and mutation landscape. Thus, they represent the only reliable model for human liver cancer up to now. However, despite their utility and predictive value, PDXs are not amenable for large drug testing (20 drugs at a time) as they would require many animals and resources.

An alternative to that, would be the development of primary liver cancer cultures that could expand long-term, be easy to manipulate and where to perform large drug screening tests (>20 compounds at a time), in a timely manner since the collection of the specimen from the patient. However, primary liver cells have proven challenging to expand in culture.

We have recently described that human liver healthy tissue can be cultured and expanded long-term in vitro, into genetically stable 3D-structures that we have termed "liver organoids". Using this technology we have successfully modelled 2 human liver monogenic diseases: Alpha-1 Anti-trypsin and Allagile Synrome. Here we aim at obtaining liver cancer organoids directly from the patient's tumour biopsy. This will facilitate assaying personalized anti-cancer therapeutic strategies and studying human liver cancer biology. As a consequence, our project will replace the use of animals in liver cancer research and drug testing thus significantly impacting on the application of the 3Rs.

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Project grant

Status:

Not yet active

Principal investigator

Dr Meritxell Huch

Institution

University of Cambridge

Grant reference number

NC/R001162/1

Award date:

Aug 2017 - Jan 2020

Grant amount

£218,178